The present invention relates to building management.
Modern commercial buildings contain a wide variety of machinery such as lifts, heating systems, lighting systems, air-conditioning systems and window cleaning systems etc. Typically, facilities managers within these buildings have dealt with equipment failures by logging a telephone call with a maintenance contracting company that responds by sending an individual to the building to diagnose and repair the fault.
In this specification we refer to the term “site events” to describe any event relating to the status of a building, its visitors or its equipment including without limitation the fact of a breakdown, the making of a fault report or repair request, the visit of an engineer on a planned maintenance visit or in response to a site request or the return to service of faulty equipment. Good building management requires the monitoring of these site events.
One type of site event—the tracking of visitors to buildings has, in the past, generally been by utilising log books and security sign-in forms etc to verify attendance at a building by parties such as maintenance contractors, insurance surveyors, consultants and others. More recently security systems have become fully computerised and building managers etc can make use of data about employees and others' entries and exits to a given building although without easily logging the purpose of such visits. The analysis of records of visits, time on site etc has for that reason been typically a painstakingly slow, inefficient and expensive analysis of manual records or, if computerised, suffering from an inability to link up multiple sites, buildings and types of visitors etc.
Therefore, systems do not exist to securely record information relating to events that occur in a building such as reporting equipment faults and status changes relating thereto, for example, whether a maintenance contractor has been called, their response time to arrive on site, time spent on site and the outcome of their visit etc. This creates an added level of complexity for data collection and analysis.